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Python
Machine Learning (ML)JOB DETAILS:
* Job Title: Principal Data Scientist
* Industry: Healthcare
* Salary: Best in Industry
* Experience: 6-10 years
* Location: Bengaluru
Preferred Skills: Generative AI, NLP & ASR, Transformer Models, Cloud Deployment, MLOps
Criteria:
- Candidate must have 7+ years of experience in ML, Generative AI, NLP, ASR, and LLMs (preferably healthcare).
- Candidate must have strong Python skills with hands-on experience in PyTorch/TensorFlow and transformer model fine-tuning.
- Candidate must have experience deploying scalable AI solutions on AWS/Azure/GCP with MLOps, Docker, and Kubernetes.
- Candidate must have hands-on experience with LangChain, OpenAI APIs, vector databases, and RAG architectures.
- Candidate must have experience integrating AI with EHR/EMR systems, ensuring HIPAA/HL7/FHIR compliance, and leading AI initiatives.
Job Description
Principal Data Scientist
(Healthcare AI | ASR | LLM | NLP | Cloud | Agentic AI)
Job Details
- Designation: Principal Data Scientist (Healthcare AI, ASR, LLM, NLP, Cloud, Agentic AI)
- Location: Hebbal Ring Road, Bengaluru
- Work Mode: Work from Office
- Shift: Day Shift
- Reporting To: SVP
- Compensation: Best in the industry (for suitable candidates)
Educational Qualifications
- Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- Technical certifications in AI/ML, NLP, or Cloud Computing are an added advantage
Experience Required
- 7+ years of experience solving real-world problems using:
- Natural Language Processing (NLP)
- Automatic Speech Recognition (ASR)
- Large Language Models (LLMs)
- Machine Learning (ML)
- Preferably within the healthcare domain
- Experience in Agentic AI, cloud deployments, and fine-tuning transformer-based models is highly desirable
Role Overview
This position is part of company, a healthcare division of Focus Group specializing in medical coding and scribing.
We are building a suite of AI-powered, state-of-the-art web and mobile solutions designed to:
- Reduce administrative burden in EMR data entry
- Improve provider satisfaction and productivity
- Enhance quality of care and patient outcomes
Our solutions combine cutting-edge AI technologies with live scribing services to streamline clinical workflows and strengthen clinical decision-making.
The Principal Data Scientist will lead the design, development, and deployment of cognitive AI solutions, including advanced speech and text analytics for healthcare applications. The role demands deep expertise in generative AI, classical ML, deep learning, cloud deployments, and agentic AI frameworks.
Key Responsibilities
AI Strategy & Solution Development
- Define and develop AI-driven solutions for speech recognition, text processing, and conversational AI
- Research and implement transformer-based models (Whisper, LLaMA, GPT, T5, BERT, etc.) for speech-to-text, medical summarization, and clinical documentation
- Develop and integrate Agentic AI frameworks enabling multi-agent collaboration
- Design scalable, reusable, and production-ready AI frameworks for speech and text analytics
Model Development & Optimization
- Fine-tune, train, and optimize large-scale NLP and ASR models
- Develop and optimize ML algorithms for speech, text, and structured healthcare data
- Conduct rigorous testing and validation to ensure high clinical accuracy and performance
- Continuously evaluate and enhance model efficiency and reliability
Cloud & MLOps Implementation
- Architect and deploy AI models on AWS, Azure, or GCP
- Deploy and manage models using containerization, Kubernetes, and serverless architectures
- Design and implement robust MLOps strategies for lifecycle management
Integration & Compliance
- Ensure compliance with healthcare standards such as HIPAA, HL7, and FHIR
- Integrate AI systems with EHR/EMR platforms
- Implement ethical AI practices, regulatory compliance, and bias mitigation techniques
Collaboration & Leadership
- Work closely with business analysts, healthcare professionals, software engineers, and ML engineers
- Implement LangChain, OpenAI APIs, vector databases (Pinecone, FAISS, Weaviate), and RAG architectures
- Mentor and lead junior data scientists and engineers
- Contribute to AI research, publications, patents, and long-term AI strategy
Required Skills & Competencies
- Expertise in Machine Learning, Deep Learning, and Generative AI
- Strong Python programming skills
- Hands-on experience with PyTorch and TensorFlow
- Experience fine-tuning transformer-based LLMs (GPT, BERT, T5, LLaMA, etc.)
- Familiarity with ASR models (Whisper, Canary, wav2vec, DeepSpeech)
- Experience with text embeddings and vector databases
- Proficiency in cloud platforms (AWS, Azure, GCP)
- Experience with LangChain, OpenAI APIs, and RAG architectures
- Knowledge of agentic AI frameworks and reinforcement learning
- Familiarity with Docker, Kubernetes, and MLOps best practices
- Understanding of FHIR, HL7, HIPAA, and healthcare system integrations
- Strong communication, collaboration, and mentoring skills
2-5 yrs of proven experience in ML, DL, and preferably NLP.
Preferred Educational Background - B.E/B.Tech, M.S./M.Tech, Ph.D.
𝐖𝐡𝐚𝐭 𝐰𝐢𝐥𝐥 𝐲𝐨𝐮 𝐰𝐨𝐫𝐤 𝐨𝐧?
𝟏) Problem formulation and solution designing of ML/NLP applications across complex well-defined as well as open-ended healthcare problems.
2) Cutting-edge machine learning, data mining, and statistical techniques to analyse and utilise large-scale structured and unstructured clinical data.
3) End-to-end development of company proprietary AI engines - data collection, cleaning, data modelling, model training / testing, monitoring, and deployment.
4) Research and innovate novel ML algorithms and their applications suited to the problem at hand.
𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐰𝐞 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐟𝐨𝐫?
𝟏) Deeper understanding of business objectives and ability to formulate the problem as a Data Science problem.
𝟐) Solid expertise in knowledge graphs, graph neural nets, clustering, classification.
𝟑) Strong understanding of data normalization techniques, SVM, Random forest, data visualization techniques.
𝟒) Expertise in RNN, LSTM, and other neural network architectures.
𝟓) DL frameworks: Tensorflow, Pytorch, Keras
𝟔) High proficiency with standard database skills (e.g., SQL, MongoDB, Graph DB), data preparation, cleaning, and wrangling/munging.
𝟕) Comfortable with web scraping, extracting, manipulating, and analyzing complex, high-volume, high-dimensionality data from varying sources.
𝟖) Experience with deploying ML models on cloud platforms like AWS or Azure.
9) Familiarity with version control with GIT, BitBucket, SVN, or similar.
𝐖𝐡𝐲 𝐜𝐡𝐨𝐨𝐬𝐞 𝐮𝐬?
𝟏) We offer Competitive remuneration.
𝟐) We give opportunities to work on exciting and cutting-edge machine learning problems so you contribute towards transforming the healthcare industry.
𝟑) We offer flexibility to choose your tools, methods, and ways to collaborate.
𝟒) We always value and believe in new ideas and encourage creative thinking.
𝟓) We offer open culture where you will work closely with the founding team and have the chance to influence the product design and execution.
𝟔) And, of course, the thrill of being part of an early-stage startup, launching a product, and seeing it in the hands of the users.
Deep LearningPythonMachine Learning (ML)WE ARE GRAPHENE
Graphene is an award-winning AI company, developing customized insights and data solutions for corporate clients. With a focus on healthcare, consumer goods and financial services, our proprietary AI platform is disrupting market research with an approach that allows us to get into the mind of customers to a degree unprecedented in traditional market research.
Graphene was founded by corporate leaders from Microsoft and P&G and works closely with the Singapore Government & universities in creating cutting edge technology. We are gaining traction with many Fortune 500 companies globally.
Graphene has a 6-year track record of delivering financially sustainable growth and is one of the few start-ups which are self-funded, yet profitable and debt free.
We already have a strong bench strength of leaders in place. Now, we are looking to groom more talents for our expansion into the US. Join us and take both our growths to the next level!
WHAT WILL THE ENGINEER-ML DO?
- Primary Purpose: As part of a highly productive and creative AI (NLP) analytics team, optimize algorithms/models for performance and scalability, engineer & implement machine learning algorithms into services and pipelines to be consumed at web-scale
- Daily Grind: Interface with data scientists, project managers, and the engineering team to achieve sprint goals on the product roadmap, and ensure healthy models, endpoints, CI/CD,
- Career Progression: Senior ML Engineer, ML Architect
YOU CAN EXPECT TO
- Work in a product-development team capable of independently authoring software products.
- Guide junior programmers, set up the architecture, and follow modular development approaches.
- Design and develop code which is well documented.
- Optimize of the application for maximum speed and scalability
- Adhere to the best Information security and Devops practices.
- Research and develop new approaches to problems.
- Design and implement schemas and databases with respect to the AI application
- Cross-pollinated with other teams.
HARD AND SOFT SKILLS
Must Have
- Problem-solving abilities
- Extremely strong programming background – data structures and algorithm
- Advanced Machine Learning: TensorFlow, Keras
- Python, spaCy, NLTK, Word2Vec, Graph databases, Knowledge-graph, BERT (derived models), Hyperparameter tuning
- Experience with OOPs and design patterns
- Exposure to RDBMS/NoSQL
- Test Driven Development Methodology
Good to Have
- Working in cloud-native environments (preferably Azure)
- Microservices
- Enterprise Design Patterns
- Microservices Architecture
- Distributed Systems
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